Flow cytometry has come of age; it is now being used as a tool for systems biology research based on its unique ability to monitor a large number of parameters within individual cells.

At the recent ELRIG conference “BioPharmaceuticals Flow Cytometry & Imaging”, speakers presented their solutions to the challenges faced by researchers that are looking to exploit the resolution of flow cytometry to address biological questions within the context of systems biology complexity.

Driven by the desire to use the flow cytometer as a high-throughput, high-content instrument for the screening of cell-signaling pathways in single cells, Bernd Bodenmiller, Ph.D., group leader at the University of Zurich, and his lab employ mass cytometry, a novel technology that increases the number of parameters that could be resolved from 10–12 to up to 100.

During his postdoctoral time at Stanford University, Dr. Bodenmiller and colleagues developed a technology called mass-tag cellular barcoding (MCB), which enabled them to pool cell subpopulations plated in a 96-well plate.

Each plate position contained a unique set of stable metal isotopes that can be used to label cells in each well. In a process not unlike the labeling of cells with fluorescently tagged antibodies, the mass tags are introduced into the cells via a small molecule compound, which binds the metal isotopes and covalently binds to cellular proteins.

These metal tags (barcodes) can then be used in the mass cytometer to identify the source of the cell under interrogation using fluorescent tags. In the mass cytometer, only seven channels are needed to resolve the barcodes from a 96-well plate, which leaves more than 30 channels to resolve cell-surface markers and differentiate cellular markers from intracellular epitopes.

“The example we use to illustrate the power of this approach is the interrogation of phosphorylation patterns in peripheral blood monocytes,” explained Dr. Bodenmiller.

“We are able to differentiate phosphorylation patterns in 14 different cell types, looking at 14 different phosphorylation sites after exposing the cells to small molecule kinase inhibitors that target the active site in the kinase (e.g., rapamycin) provided in eight different drug concentrations and 12 different cellular conditions, which yields 18,816 measured phosphorylation levels in a single measurement.”

What the lab has been able to learn from this exercise is that some expected patterns of phosphorylation can be observed. Specifically, closely related cell types respond similarly to inhibition by known compounds based on previous analysis using these cell types and the particular drugs under analysis. But in addition, novel patterns were revealed, which allows the lab to group unknown compounds with known ones with respect to mechanism of inhibition and the site of action.

“The other benefit of using MCB prior to antibody staining with fluorescent tags is that throughput goes up to thousands of samples per day, the costs of antibody are significantly reduced, and the quality of the data increases due to homogenous cell labeling,” concluded Dr. Bodenmiller.

Making the Data Meaningful

Collecting data is one achievement, but the next step is to reduce it to a useful level that can be interacted with and manipulated directly by the biologist.

Analogous to the analysis of gene expression arrays, you can’t understand the whole array by analyzing only a few spots independently. In the same way, you can’t interrogate complex biology by analyzing a single sample at a time. High-content screening by flow cytometry must involve the analysis of multiple samples from multiple cell sources.

“Flow cytometry has the unique capacity to look at single cells,” shared Paul Robinson, Ph.D., SVM professor of cytometics and professor of biomedical engineering, Purdue University. “Using standard labeling protocols, it is possible to perform three assays per well on a 384-well plate and process that on the flow cytometer within an 8-minute timeframe. We have automated all the steps from sample prep to sample loading (from 96-, 384- to 1,536-well plates) and now finally complete analysis.

“We have used K562, HEL60 cell lines and primary cells, including lymphocytes from blood draws. Setting up HTS analyses, we have designed mitochondrial tox assays, including the measurement of membrane potential, cell viability, and glutathione levels. We routinely perform 10-point dose response curves to generate IC50 curves.”

The fundamental problem is that when you move into the systems biology space, the data content is enormous. The difficulty of collecting large sample numbers has been solved by robotics, and the analytical solutions become the major problem when dealing with thousands of flow cytometry datasets.

“The data analysis side of the ‘HTS problem’ has been solved using an icon-based workflow. We provide that to academic labs for free,” shared Dr. Robinson. “Biopharma customers are welcome to discuss collaborative opportunities.”

Melanoma Xenografts in Zebrafish

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This series of images shows the site of injection in a Flk-GFP zebrafish embryo that expresses GFP in the endothelial cells allowing visualization of the circulatory system. The red cells are the melanoma cells that have been injected in the zebrafish embryo. [University of Manchester]

Anna Chapman, Ph.D., a post-doctoral researcher at the University of Manchester, developed a zebrafish model for human melanoma xenografts for the study of tumorigenesis. Human melanoma cells are injected into two-day-old zebrafish embryos and monitored five days later. By virtue of the small size of the embryos and their transparency, they are amenable to both FACs sorting and imaging using confocal microscopy.

“The key question we are addressing by this work is how different melanoma cells interact with each other with respect to their invasive character,” explained Dr. Chapman. “The working hypothesis is that the microenvironment—and in particular, the extracellular matrix—plays a significant role in the progression of tumor development and cellular invasion.”

Immunofluorescence with antibodies directed against human antigens picks out the melanoma xenograft in whole zebrafish embryos. Sorting of 100–150 embryos can easily be done, setting up gene expression analysis following homogenization of the embryos and extraction of the human melanoma cells.

Confocal microscopy is used to image individual embryos to look at proliferation of co-cultures and invasion of tissues away from the primary injection site. Data collected over the one-week period of the analysis from the disparate approaches is pulled together to develop the final systems biology story. This system is amenable to the study of other solid tumors (e.g., breast cancer cell lines) and to assess the efficacy of targeted therapies.

Autophagy Detection in Primary Cells

“Autophagy is a conserved constitutive cellular process, responsible for the degradation of dysfunctional proteins and organelles,” said Katja Simon, Ph.D., university research lecturer, Oxford University. “Autophagy plays a role in many diseases such as neurodegeneration and cancer. However to date, conventional autophagy detection techniques are not suitable for clinical samples. We have developed a high-throughput, statistically robust technique that quantitates autophagy in primary human leukocytes using the ImageStream (Amnis).

“As it relates to aging, our results indicate that healthy primary senescent CD8+ T cells have decreased autophagic levels correlating with increased DNA damage, which may explain features of the senescent immune system and its declining function with age. This technique will also allow us to measure autophagy levels in diseases with a known link to autophagy, while determining the contribution of autophagy to the efficacy of drugs.

“The ImageStream system allows the lab to monitor the co-localization of two fluorescent labels for the two vesicles formed to complete autophagy; the autophagasome and the lysosome fuse to initiate the degradation and recycling of the cytoplasmic components or organelles. We use an antibody against the LC3 marker, a molecule in the membrane of an autophagasome, and LysosomeID as a marker for lysosomes.

“In primary cells, it is possible to compare the rates of autophagy in untreated vs. treated cells,” continued Dr. Simon. “The assay involves isolating primary cells from the circulation, starving them by growth in EBSS to induce autophagy, and then adding lysosomal inhibitors to block completion of the process, enabling autolysosome accumulation.”

In disease states like Parkinson’s, autophagy has been shown to play a role. Protein aggregates that accumulate in neurons lead to their dysfunction. Since whole-protein aggregates are best degraded in the autophagy pathway, any diminution of autophagy would result in accumulation of protein aggregates.

Because it is thought that Parkinson’s has a genetic component, it is possible to use blood as a surrogate tissue for neurons in patients to test for rates of autophagy. Current work in progress is studying blood samples from Parkinson’s patients with the specific mutations for their rates of autophagy in blood samples.

Cancer is a much more complicated story. In mouse models, knockouts of the autophagy pathway have a higher incidence of AML. But given the higher proliferative growth rates of cancer cells, the expectation is that this high rate of proliferation leads to stress, hypoxia, and nutrient starvation, all of which are expected to turn on autophagy. Currently there are at least 30 clinical trials looking at autophagy inhibitors as a cancer therapeutic.

While there are no clean assay systems to date, researchers in the Simon lab are looking to demonstrate the utility of their imaging flow-based assay for monitoring autophagy in blood cancers before and after treatment.

Finding the Right Haystack

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The S3™ cell sorter features automated setup and monitoring, making it easy to use while maintaining high performance and sensitivity, according to Bio-Rad.

Customer feedback led Bio-Rad to search for a simple solution for isolation of subpopulations of cells, or even the isolation of single cells for subsequent analysis. Bio-Rad officials say they found the answer in Propel Labs’ Avalon instrument, which Bio-Rad will commercialize as the S3™ cell sorter.

“Bio-Rad is focused on making technology accessible to biologists who just want to get an answer to the complex biological system they are working to understand,” says Brad Crutchfield, president of the life science group at Bio-Rad. “The S3 provides biologists with a solution that has been previously unmet in the marketplace. When it comes to supporting experimental workflow in a simple solution, the key is to know what haystack to look in.”

“Propel Labs has extensive knowledge in flow cytometry and cell sorting,” adds Tidhar Sadeh, president of Propel Labs. “We wanted to build a benchtop sorter from the ground up that would enable biologists access to a simple solution that wouldn’t require expertise in flow cytometry. We’ve built an intuitive instrument with an application-specific focus.”

Propel Labs is now involved in the knowledge transfer and will continue to partner with Bio-Rad R&D on engineering projects including software to make sure that the S3 stays ahead of the curve for delivery of ease-of-use specs and customer-specified application solutions.

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